We design and develop microservices architectures for companies that need to scale their corporate applications independently, deploy more frequently and build resilient systems that do not fail in cascade. From architecture design and API contract definition to Kubernetes deployment and monitoring with full observability.
Microservices Development for Corporate Applications
At MiT Software we design and develop microservices architectures for organizations that have outgrown the limitations of their monolithic applications and need an architectural model that allows multiple teams to work in parallel, deploy independently and scale each component according to its real demand. Microservices are not the right solution for every project — they require significant organizational and technical maturity — but when applied in the right context, they transform an organization ability to innovate, scale and operate its systems efficiently. Our experience spans architecture design, service development with Java Spring Boot and Node.js, containerization with Docker, deployment in Kubernetes and the implementation of all the patterns needed to operate microservices with confidence in production.
Before recommending microservices, we honestly assess whether they are the right solution for your organization. Microservices require significant organizational and technical maturity — DevOps culture, CI/CD automation, distributed systems experience — and are not the right answer for all problems. If a well-structured monolith is the better option, we say so.
We run Event Storming and Domain-Driven Design workshops with technical and business teams to identify business subdomains, define bounded contexts and design microservice boundaries that reflect the real domain structure and minimize coupling between services.
We start by developing the first microservice together with all the necessary support infrastructure: CI/CD pipeline, containerization, Kubernetes deployment, observability and communication patterns. This first service serves as reference and validation of the architectural patterns before extending the model to the rest of the services.
For organizations migrating from an existing monolithic application, we apply the Strangler Fig pattern: extracting the most suitable domains from the monolith incrementally, one by one, keeping the monolith in production throughout the process and gradually reducing its size without interrupting service at any time.
We deploy microservices in the production environment with high availability configurations, autoscaling and canary or blue-green deployment strategies that allow launching new versions with minimal risk. We train operations teams in Kubernetes cluster management and the use of observability tools.
We provide continuous support for the evolution of the microservices architecture: incorporation of new services, refactoring of existing services, performance optimization, dependency updates and production incident resolution. The goal is for your organization to progressively build the internal capacity to operate and evolve the architecture autonomously.
In a monolithic application, if one component needs more capacity you have to scale the entire application. With microservices, each service scales independently: if the payment service needs more capacity during peak hours, only that service scales, without affecting the rest of the system and without over-provisioning unnecessary resources.
One of the biggest advantages of microservices is organizational: each team owns one or more services, deploys independently and can evolve its part of the system without coordinating with other teams. This multiplies the development velocity of large organizations and eliminates the deployment bottleneck that paralyzes teams with large monoliths.
We apply Domain-Driven Design (DDD) to identify the bounded contexts of the business and define the correct boundaries of each microservice. A bad decomposition of services generates a distributed monolith with all the problems of both worlds — we ensure that each service has a clear responsibility and minimizes coupling with the rest.
We develop microservices with the most appropriate technology for each use case: Java Spring Boot for services that require high performance, strong typing and a mature ecosystem; Node.js for services that need high concurrency and fast I/O; and Python for services that incorporate machine learning or AI capabilities.
We design and implement the inter-service communication patterns appropriate for each interaction: synchronous REST APIs for request-response interactions, gRPC for high-performance internal communications and asynchronous messaging with Kafka or RabbitMQ for event-driven interactions that decouple services.
We implement an API Gateway that centralizes all inbound traffic to the microservices ecosystem: request routing, authentication and authorization, rate limiting, SSL termination, request transformation and centralized observability. We work with Kong, AWS API Gateway, Azure API Management or NGINX depending on your infrastructure.
We containerize all microservices with Docker, creating reproducible images that work identically in all environments. We deploy them in Kubernetes, configuring deployments, services, ingress, resource limits, health checks, horizontal autoscaling and deployment strategies — canary or blue-green — for risk-free production deployments.
In a microservices environment, a single user request can traverse dozens of services. We implement complete observability: distributed tracing with Jaeger or Zipkin to follow a request through all services, metrics with Prometheus and Grafana for performance monitoring, and centralized logging with the ELK stack or Loki.
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